analyze-ci-speed

2
1
Source

Analyze compilation time and test durations from CI logs. Use when the user asks about slow builds, slow tests, or wants to optimize CI time.

Install

mkdir -p .claude/skills/analyze-ci-speed && curl -L -o skill.zip "https://mcp.directory/api/skills/download/6085" && unzip -o skill.zip -d .claude/skills/analyze-ci-speed && rm skill.zip

Installs to .claude/skills/analyze-ci-speed

About this skill

Analyze CI Speed

Analyze compilation time and test durations from CI logs to identify optimization opportunities.

Prerequisites

  • gh CLI installed and authenticated (gh auth login)

Instructions

Step 1: Get Recent Workflow Runs

Get latest successful run from dev branch:

gh run list --workflow=Rust --branch=dev --limit=1 --status=success --json databaseId,conclusion,headSha,createdAt

Step 2: Download Test Job Logs

Get test jobs (nextest, nextest_all_features, coverage):

gh run view <run-id> --json jobs --jq '.jobs[] | select(.name == "nextest" or .name == "nextest_all_features" or .name == "coverage") | {id: .databaseId, name: .name}'

Download logs, stripping ANSI codes:

mkdir -p ci-logs/speed-analysis/
gh run view --job <job-id> --log | perl -pe 's/\e\[[0-9;]*m//g' > ci-logs/speed-analysis/<job_name>.log

Step 3: Extract Compilation Time

Search for cargo build summary in logs:

Finished ... in Xm Ys

Also look for incremental compilation info and cache hit rates.

Step 4: Extract Test Durations

Parse nextest output for test durations. Look for patterns like:

PASS [   1.234s] crate_name::module::test_name
SLOW [  15.678s] crate_name::module::slow_test

Extract all test durations and sort to find top 10 slowest tests.

Step 5: Analyze and Report

Provide summary:

  • Total compilation time
  • Top 10 slowest tests with durations
  • Any tests marked as SLOW by nextest
  • Recommendations:
    • Tests that could be optimized or parallelized
    • Crates with long compilation times
    • Potential for better caching

Notes

  • Run on successful builds to get complete timing data
  • Compare across runs to identify regressions

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